本文整理汇总了Python中numpy.core.umath.e方法的典型用法代码示例。如果您正苦于以下问题：Python umath.e方法的具体用法？Python umath.e怎么用？Python umath.e使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类numpy.core.umath的用法示例。
在下文中一共展示了umath.e方法的7个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_ignore_object_identity_in_equal
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_ignore_object_identity_in_equal(self):
# Check error raised when comparing identical objects whose comparison
# is not a simple boolean, e.g., arrays that are compared elementwise.
a = np.array([np.array([1, 2, 3]), None], dtype=object)
assert_raises(ValueError, np.equal, a, a)
# Check error raised when comparing identical non-comparable objects.
class FunkyType(object):
def __eq__(self, other):
raise TypeError("I won't compare")
a = np.array([FunkyType()])
assert_raises(TypeError, np.equal, a, a)
# Check identity doesn't override comparison mismatch.
a = np.array([np.nan], dtype=object)
assert_equal(np.equal(a, a), [False]) 示例2: test_ignore_object_identity_in_not_equal
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_ignore_object_identity_in_not_equal(self):
# Check error raised when comparing identical objects whose comparison
# is not a simple boolean, e.g., arrays that are compared elementwise.
a = np.array([np.array([1, 2, 3]), None], dtype=object)
assert_raises(ValueError, np.not_equal, a, a)
# Check error raised when comparing identical non-comparable objects.
class FunkyType(object):
def __ne__(self, other):
raise TypeError("I won't compare")
a = np.array([FunkyType()])
assert_raises(TypeError, np.not_equal, a, a)
# Check identity doesn't override comparison mismatch.
a = np.array([np.nan], dtype=object)
assert_equal(np.not_equal(a, a), [True]) 示例3: test_e
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_e(self):
assert_allclose(ncu.e, 2.718281828459045, 1e-15) 示例4: test_division_complex
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_division_complex(self):
# check that implementation is correct
msg = "Complex division implementation check"
x = np.array([1. + 1.*1j, 1. + .5*1j, 1. + 2.*1j], dtype=np.complex128)
assert_almost_equal(x**2/x, x, err_msg=msg)
# check overflow, underflow
msg = "Complex division overflow/underflow check"
x = np.array([1.e+110, 1.e-110], dtype=np.complex128)
y = x**2/x
assert_almost_equal(y/x, [1, 1], err_msg=msg) 示例5: test_floor_division_complex
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_floor_division_complex(self):
# check that implementation is correct
msg = "Complex floor division implementation check"
x = np.array([.9 + 1j, -.1 + 1j, .9 + .5*1j, .9 + 2.*1j], dtype=np.complex128)
y = np.array([0., -1., 0., 0.], dtype=np.complex128)
assert_equal(np.floor_divide(x**2, x), y, err_msg=msg)
# check overflow, underflow
msg = "Complex floor division overflow/underflow check"
x = np.array([1.e+110, 1.e-110], dtype=np.complex128)
y = np.floor_divide(x**2, x)
assert_equal(y, [1.e+110, 0], err_msg=msg) 示例6: test_lower_align
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_lower_align(self):
# check data that is not aligned to element size
# i.e doubles are aligned to 4 bytes on i386
d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64)
assert_equal(np.abs(d), d)
assert_equal(np.negative(d), -d)
np.negative(d, out=d)
np.negative(np.ones_like(d), out=d)
np.abs(d, out=d)
np.abs(np.ones_like(d), out=d) 示例7: test_lower_align
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import e [as 别名]
def test_lower_align(self):
# check data that is not aligned to element size
# i.e doubles are aligned to 4 bytes on i386
d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64)
assert_equal(d.max(), d[0])
assert_equal(d.min(), d[0])